Instructions to use ZeroAgency/Zero-Mistral-Small-24B-Instruct-2501-F16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ZeroAgency/Zero-Mistral-Small-24B-Instruct-2501-F16 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="ZeroAgency/Zero-Mistral-Small-24B-Instruct-2501-F16") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ZeroAgency/Zero-Mistral-Small-24B-Instruct-2501-F16", dtype="auto") - llama-cpp-python
How to use ZeroAgency/Zero-Mistral-Small-24B-Instruct-2501-F16 with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="ZeroAgency/Zero-Mistral-Small-24B-Instruct-2501-F16", filename="Zero-Mistral-Small-24B-Instruct-2501-F16.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use ZeroAgency/Zero-Mistral-Small-24B-Instruct-2501-F16 with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf ZeroAgency/Zero-Mistral-Small-24B-Instruct-2501-F16:F16 # Run inference directly in the terminal: llama-cli -hf ZeroAgency/Zero-Mistral-Small-24B-Instruct-2501-F16:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf ZeroAgency/Zero-Mistral-Small-24B-Instruct-2501-F16:F16 # Run inference directly in the terminal: llama-cli -hf ZeroAgency/Zero-Mistral-Small-24B-Instruct-2501-F16:F16
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf ZeroAgency/Zero-Mistral-Small-24B-Instruct-2501-F16:F16 # Run inference directly in the terminal: ./llama-cli -hf ZeroAgency/Zero-Mistral-Small-24B-Instruct-2501-F16:F16
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf ZeroAgency/Zero-Mistral-Small-24B-Instruct-2501-F16:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf ZeroAgency/Zero-Mistral-Small-24B-Instruct-2501-F16:F16
Use Docker
docker model run hf.co/ZeroAgency/Zero-Mistral-Small-24B-Instruct-2501-F16:F16
- LM Studio
- Jan
- vLLM
How to use ZeroAgency/Zero-Mistral-Small-24B-Instruct-2501-F16 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ZeroAgency/Zero-Mistral-Small-24B-Instruct-2501-F16" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ZeroAgency/Zero-Mistral-Small-24B-Instruct-2501-F16", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/ZeroAgency/Zero-Mistral-Small-24B-Instruct-2501-F16:F16
- SGLang
How to use ZeroAgency/Zero-Mistral-Small-24B-Instruct-2501-F16 with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "ZeroAgency/Zero-Mistral-Small-24B-Instruct-2501-F16" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ZeroAgency/Zero-Mistral-Small-24B-Instruct-2501-F16", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "ZeroAgency/Zero-Mistral-Small-24B-Instruct-2501-F16" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ZeroAgency/Zero-Mistral-Small-24B-Instruct-2501-F16", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Ollama
How to use ZeroAgency/Zero-Mistral-Small-24B-Instruct-2501-F16 with Ollama:
ollama run hf.co/ZeroAgency/Zero-Mistral-Small-24B-Instruct-2501-F16:F16
- Unsloth Studio new
How to use ZeroAgency/Zero-Mistral-Small-24B-Instruct-2501-F16 with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for ZeroAgency/Zero-Mistral-Small-24B-Instruct-2501-F16 to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for ZeroAgency/Zero-Mistral-Small-24B-Instruct-2501-F16 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for ZeroAgency/Zero-Mistral-Small-24B-Instruct-2501-F16 to start chatting
- Docker Model Runner
How to use ZeroAgency/Zero-Mistral-Small-24B-Instruct-2501-F16 with Docker Model Runner:
docker model run hf.co/ZeroAgency/Zero-Mistral-Small-24B-Instruct-2501-F16:F16
- Lemonade
How to use ZeroAgency/Zero-Mistral-Small-24B-Instruct-2501-F16 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull ZeroAgency/Zero-Mistral-Small-24B-Instruct-2501-F16:F16
Run and chat with the model
lemonade run user.Zero-Mistral-Small-24B-Instruct-2501-F16-F16
List all available models
lemonade list
Zero-Mistral-Small-24B-Instruct-2501 F16 GGUF version
Zero-Mistral-Small is an improved version of mistralai/Mistral-Small-24B-Instruct-2501, primarily adapted for Russian and English languages. The training involved SFT stage on GrandMaster-PRO-MAX dataset.
📚 Model versions
- Merged 16-bit - original 16bit merged version.
- LoRa adapter for mistralai/Mistral-Small-24B-Instruct-2501
- F16 GGUF
- BF16 GGUF
- Q8_0 GGUF
- Q4_K_M GGUF
- Downloads last month
- 1
16-bit
Model tree for ZeroAgency/Zero-Mistral-Small-24B-Instruct-2501-F16
Base model
mistralai/Mistral-Small-24B-Base-2501